Over the last years, network analysis has become an active topic of research, with numerous applications in macroeconomics and finance. In a nutshell, network analysis is concerned with representing the interconnections of a large panel as a graph: the vertices of the graph represent the variables in the panel, and the presence of an edge between two vertices denotes the presence of some appropriate measure of dependence between the two variables. Dependence can derive from direct exposures or from indirect or common exposures.

From an economic perspective, the interest on networks has been boosted by the research of, inter alia, Acemoglu et al. (2012), which shows that individual entities can have a non-negligible effect on the aggregate behavior of the economy when the system has a high degree of interconnectedness. Especially since the 2008 global financial crisis, the interest in analyzing the role of network structure in transmitting – or dissipating – stress has grown significantly. This work is concerned with the theory and practice of network analysis techniques for applications in finance and economics.

Christian Brownlees is an Associate Professor in the Department of Economics and Business at the Universitat Pompeu Fabra. Christian received his PhD in Statistics and B.S. in Economics and Quantitative Methods from Universita’ di Firenze. He was also a visiting PhD researcher at UCSD and post-doc researcher at NYU. Christian’s research lays at the intersection of statistics, econometrics, economics and finance. In particular, his research focuses on volatility and systemic risk. Christian has published in the Journal of Econometrics, the Review of Economics and Statistics, Annals of Statistics and the Review of Financial Studies.

Iman van Lelyveld is a Senior Policy Advisor with DNB’s Statistics Division and Professor of Banking and Financial Markets at the Finance Group of the VU Amsterdam. At DNB he is spearheading the Data Science Hub initiative. He has published widely on international banking and financial networks. He has worked for Deutsche Bank, the Bank of England, and the International Data Hub at the Bank for International Settlements (BIS). At the BIS he helped to setup analysis of the exposure network of the largest banks in the world.

Adrien Amzallag (European Securities and Markets Authority)
Adrien Amzallag works on risk analysis and structured finance policy topics at the European Securities and Markets Authority. Before joining ESMA, Adrien worked for many years at the European Central Bank on structured finance, risk management, and financial stability activities. Adrien holds degrees in Economics from the London School of Economics and the University of Edinburgh.

Marco d’Errico (European Systemic Risk Board)
Marco D’Errico is a Senior Financial Stability Expert in the European Systemic Risk Board Secretariat at the European Central Bank where he works on data analytics, interconnectedness and contagion. Prior to joining the ECB, Marco was a researcher at the University of Zurich, where he was involved in several EU project related to systemic risk, financial stability and sustainable finance. He holds a PhD in Financial Mathematics from the University of Milan – Bicocca.

Natalie Kessler (European University Institute)
Natalie Kessler is a 4th year PhD candidate in economics at the European University Institute (EUI). In her thesis, she focuses on various issues in financial economics with an overall focus on financial stability enhancing regulations. Working mainly theoretical, she explores both micro- and macro-economic issues. Her main research interests are unconventional monetary policy, financial market structure and bank competition, over-the-counter trading, and banks’ optimal capital allocations. Before coming to the EUI, she completed the Master in Advanced Economics and Finance at the Copenhagen Business School.

• Understand the basic concepts of network theory, including: vertices, edges, network properties, random graphs;
• Derive theoretical results about stability in interbank networks;
• Model contemporaneous dependence in large panels of time series;
• Estimate large dimensional network models (using LASSO estimation);
• Identify the reasons for contagion via indirect exposures;
• Select the most appropriate tools for the estimation of large network models;
• Distinguish between different network structures;
• Identify network structures such as hubs and communities;
• Use network models in practical policy applications.

0. Why Study Networks? [Brownlees – van Lelyveld]

1. Networks: Basic Concept [Brownlees]

2. Direct Exposure Networks [van Lelyveld]

3. Direct Contagion: the Classics [van Lelyveld]

4. Capturing Network Structure [van Lelyveld]

5. Indirect Exposure Networks [van Lelyveld]

6. Crowded Trading [van Lelyveld]

7. What are the Policy Implications? [van Lelyveld]

8. Network Models for Large Panels – Part 1 [Brownlees]

9. Network Models for Large Panels – Part 2 [Brownlees]

10. Network Models for Large Panels – Part 3 [Brownlees]

• Watch video lectures, pre-recorded (8h), mandatory
• Participate in the live classes (5h), mandatory
• Complete two exercises, mandatory
• On the platform: access to readings and discussion fora.
• Optional: One-to-one contacts with instructors in ‘virtual office hours’

Thursday 4 March 2021

1:00 – 2:15 PM (CET)
Kickoff live session (75’)

Friday 12 March

12:00 – 2:00 PM (CET)
First live session (120’)
Led by Christian Brownlees

After the live session:

• Office hours (45’)
• Exercise 1

Wednesday 17 March

12:00 – 2:00 PM (CET)
Second live session (120’)
Led by Iman van Lelyveld

After the live session:

• Office hours (45’)
• Exercise 2

Friday 19 March

1:00 – 2:00 PM
Closing live session (60’)
Policy session

5:00 PM
Deadline for submitting the quizzes.

A Master’s degree in Economics is required to attend the course.

Basic knowledge of coding in Python.

950€ – Public Authorities (e.g. National Competent Authorities, Central Banks and European Institutions).

1050€ – Private Sector.

750€ – Academics (Full-time Professors, full-time PhD Students and full-time Research Associates). Please submit a certificate attesting your status of Professor, PhD Student or Research Associate to fbf@eui.eu before registering. FBF secretariat will provide you with a code to register. *Seats for academics are limited and assigned by the FBF secretariat on a case-by-case basis.

Please note that the payment must be settled one week before the start of the course.

CANCELLATION POLICY

• Registered participants can cancel their participation and ask for a refund until three weeks (11 February) before the start of the course, by sending an email to the FBF secretariat. Past that date, refund requests will no longer be accepted by the Secretariat (unless for compelling and motivated reasons).
• In case a course is cancelled, registered participants can request a total refund or request a voucher to attend another FBF course.
• In case a course is postponed to another date, registered participants have the following three options: request a voucher to attend another FBF course, transfer their registration to a colleague or request a refund.